Clinical impact of additional findings detected by genome-wide non-invasive prenatal testing: Follow-up results of the TRIDENT-2 study.

In the TRIDENT-2 study, all pregnant women in the Netherlands are offered genome-wide non-invasive prenatal testing (GW-NIPT) with a choice of receiving either full screening or screening solely for common trisomies. Previous data showed that GW-NIPT can reliably detect common trisomies in the general obstetric population and that this test can also detect other chromosomal abnormalities (additional findings). However, evidence regarding the clinical impact of screening for additional findings is lacking. Therefore, we present follow-up results of the TRIDENT-2 study to determine this clinical impact based on the laboratory and perinatal outcomes of cases with additional findings. Between April 2017 and April 2019, additional findings were detected in 402/110,739 pregnancies (0.36%). For 358 cases, the origin was proven to be either fetal (n = 79; 22.1%), (assumed) confined placental mosaicism (CPM) (n = 189; 52.8%), or maternal (n = 90; 25.1%). For the remaining 44 (10.9%), the origin of the aberration could not be determined. Most fetal chromosomal aberrations were pathogenic and associated with severe clinical phenotypes (61/79; 77.2%). For CPM cases, occurrence of pre-eclampsia (8.5% [16/189] vs 0.5% [754/159,924]; RR 18.5), and birth weight <2.3rd percentile (13.6% [24/177] vs 2.5% [3,892/155,491]; RR 5.5) were significantly increased compared to the general obstetric population. Of the 90 maternal findings, 12 (13.3%) were malignancies and 32 (35.6%) (mosaic) pathogenic copy number variants, mostly associated with mild or no clinical phenotypes. Data from this large cohort study provide crucial information for deciding if and how to implement GW-NIPT in screening programs. Additionally, these data can inform the challenging interpretation, counseling, and follow-up of additional findings.

Health utility values of breast cancer treatments and the impact of varying quality of life assumptions on cost-effectiveness.

In breast cancer research, utility assumptions are outdated and inconsistent which may affect the results of quality adjusted life year (QALY) calculations and thereby cost-effectiveness analyses (CEAs). Four hundred sixty four female patients with breast cancer treated at Erasmus MC, the Netherlands, completed EQ-5D-5L questionnaires from diagnosis throughout their treatment. Average utilities were calculated stratified by age and treatment. These utilities were applied in CEAs analysing 920 breast cancer screening policies differing in eligible ages and screening interval simulated by the MISCAN-Breast microsimulation model, using a willingness-to-pay threshold of €20,000. The CEAs included varying sets on normative, breast cancer treatment and screening and follow-up utilities. Efficiency frontiers were compared to assess the impact of the utility sets. The calculated average patient utilities were reduced at breast cancer diagnosis and 6 months after surgery and increased toward normative utilities 12 months after surgery. When using normative utility values of 1 in CEAs, QALYs were overestimated compared to using average gender and age-specific values. Only small differences in QALYs gained were seen when varying treatment utilities in CEAs. The CEAs varying screening and follow-up utilities showed only small changes in QALYs gained and the efficiency frontier. Throughout all variations in utility sets, the optimal strategy remained robust; biennial for ages 40-76 years and occasionally biennial 40-74 years. In sum, we recommend to use gender and age stratified normative utilities in CEAs, and patient-based breast cancer utilities stratified by age and treatment or disease stage. Furthermore, despite varying utilities, the optimal screening scenario seems very robust.

Impact of different age ranges on the benefits and harms of the breast cancer screening programme by the EU-TOPIA tool.

BACKGROUND: The recommendation for the implementation of mammography screening in women aged 45-49 and 70-74 is conditional with moderate certainty of the evidence. The aim of this study is to simulate the long-term outcomes (2020-50) of using different age range scenarios in the breast cancer screening programme of the Valencia Region (Spain), considering different programme participation rates. METHODS: Three age range scenarios (S) were simulated with the EU-TOPIA tool, considering a biennial screening interval: S1, 45-69 years old (y); S2, 50-69 y and S3, 45-74 y. Simulations were performed for four participation rates: A = current participation (72.7%), B = +5%, C = +10% and D = +20%. Considered benefits: number (N°) of in situ and invasive breast cancers (BC) (screen vs. clinically detected), N° of BC deaths and % BC mortality reduction. Considered harms: N° of false positives (FP) and % overdiagnosis. RESULTS: The results showed that BC mortality decreased in all scenarios, being higher in S3A (32.2%) than S1A (30.6%) and S2A (27.9%). Harms decreased in S2A vs. S1A (N° FP: 236 vs. 423, overdiagnosis: 4.9% vs. 5.0%) but also benefits (BC mortality reduction: 27.9% vs. 30.6%, N° screen-detected invasive BC 15/28 vs. 18/25). In S3A vs. S1A, an increase in benefits was observed (BC mortality reduction: 32.2% vs. 30.6%), N° screen-detected in situ B: 5/2 vs. 4/3), but also in harms (N° FP: 460 vs. 423, overdiagnosis: 5.8% vs. 5.0%). Similar trends were observed with increased participation. CONCLUSIONS: As the age range increases, so does not only the reduction in BC mortality, but also the probability of FP and overdiagnosis.

Collaborative Modeling to Compare Different Breast Cancer Screening Strategies: A Decision Analysis for the US Preventive Services Task Force.

Importance: The effects of breast cancer incidence changes and advances in screening and treatment on outcomes of different screening strategies are not well known. Objective: To estimate outcomes of various mammography screening strategies. Design, Setting, and Population: Comparison of outcomes using 6 Cancer Intervention and Surveillance Modeling Network (CISNET) models and national data on breast cancer incidence, mammography performance, treatment effects, and other-cause mortality in US women without previous cancer diagnoses. Exposures: Thirty-six screening strategies with varying start ages (40, 45, 50 years) and stop ages (74, 79 years) with digital mammography or digital breast tomosynthesis (DBT) annually, biennially, or a combination of intervals. Strategies were evaluated for all women and for Black women, assuming 100% screening adherence and "real-world" treatment. Main Outcomes and Measures: Estimated lifetime benefits (breast cancer deaths averted, percent reduction in breast cancer mortality, life-years gained), harms (false-positive recalls, benign biopsies, overdiagnosis), and number of mammograms per 1000 women. Results: Biennial screening with DBT starting at age 40, 45, or 50 years until age 74 years averted a median of 8.2, 7.5, or 6.7 breast cancer deaths per 1000 women screened, respectively, vs no screening. Biennial DBT screening at age 40 to 74 years (vs no screening) was associated with a 30.0% breast cancer mortality reduction, 1376 false-positive recalls, and 14 overdiagnosed cases per 1000 women screened. Digital mammography screening benefits were similar to those for DBT but had more false-positive recalls. Annual screening increased benefits but resulted in more false-positive recalls and overdiagnosed cases. Benefit-to-harm ratios of continuing screening until age 79 years were similar or superior to stopping at age 74. In all strategies, women with higher-than-average breast cancer risk, higher breast density, and lower comorbidity level experienced greater screening benefits than other groups. Annual screening of Black women from age 40 to 49 years with biennial screening thereafter reduced breast cancer mortality disparities while maintaining similar benefit-to-harm trade-offs as for all women. Conclusions: This modeling analysis suggests that biennial mammography screening starting at age 40 years reduces breast cancer mortality and increases life-years gained per mammogram. More intensive screening for women with greater risk of breast cancer diagnosis or death can maintain similar benefit-to-harm trade-offs and reduce mortality disparities.

Cumulative risks of false positive recall and screen-detected breast cancer after multiple screening examinations.

Women tend to make a decision about participation in breast cancer screening and adhere to this for future invitations. Therefore, our study aimed to provide high-quality information on cumulative risks of false-positive (FP) recall and screen-detected breast cancer over multiple screening examinations. Individual Dutch screening registry data (2005-2018) were gathered on subsequent screening examinations of 92 902 women age 49 to 51 years in 2005. Survival analyses were used to calculate cumulative risks of a FP and a true-positive (TP) result after seven examinations. Data from 66 472 women age 58 to 59 years were used to extrapolate to 11 examinations. Participation, detection and additional FP rates were calculated for women who previously received FP results compared to women with true negative (TN) results. After 7 examinations, the cumulative risk of a TP result was 3.7% and the cumulative risk of a FP result was 9.1%. After 11 examinations, this increased to 7.1% and 13.5%, respectively. Following a FP result, participation was lower (71%-81%) than following a TN result (>90%). In women with a FP result, more TP results (factor 1.59 [95% CI: 1.44-1.72]), more interval cancers (factor 1.66 [95% CI: 1.41-1.91]) and more FP results (factor 1.96 [95% CI: 1.87-2.05]) were found than in women with TN results. In conclusion, due to a low recall rate in the Netherlands, the cumulative risk of a FP recall is relatively low, while the cumulative risk of a TP result is comparable. Breast cancer diagnoses and FP results were more common in women with FP results than in women with TN results, while participation was lower.

Health-related Quality of Life using the EQ-5D-5L: normative utility scores in a Dutch female population.

PURPOSE: Normative utility scores represent the health related quality of life of the general population, are of utmost importance in cost-effectiveness studies and should reflect relevant sexes and age groups. The aim of this study was to estimate EQ-5D-5L normative utility scores in a population of Dutch females, stratified by age, and to compare these scores to those of female populations of three other countries. METHODS: Dutch women completed the EQ-5D-5L online between January and July 2020. Mean normative utilities were computed using the Dutch EQ-5D-5L value set, stratified by age, tested for differences using the Kruskall-Wallis test, and compared to normative utility scores of female populations elsewhere. Additionally, to support the use of the Dutch EQ-5D-5L data in other settings, normative utility scores were also calculated by applying the value sets of Germany, United Kingdom and USA. RESULTS: Data of 9037 women were analyzed and the weighted mean utility score was 0.911 (SD 0.155, 95% CI 0.908-0.914). The mean normative utility scores differed between age groups, showing lower scores in older females. Compared to other normative utility scores of female populations, Dutch mean utilities were consistently higher except for age groups 18-24 and 25-34. With the three country-specific value sets, new age-specific mean normative utility scores were provided. CONCLUSION: This study provides mean normative utility scores of a large cohort of Dutch females per age group, which were found to be lower in older age groups. Utility scores calculated with three other value sets were made available.

Finding the optimal mammography screening strategy: A cost-effectiveness analysis of 920 modelled strategies.

Breast cancer screening policies have been designed decades ago, but current screening strategies may not be optimal anymore. Next to that, screening capacity issues may restrict feasibility. This cost-effectiveness study evaluates an extensive set of breast cancer screening strategies in the Netherlands. Using the Microsimulation Screening Analysis-Breast (MISCAN-Breast) model, the cost-effectiveness of 920 breast cancer screening strategies with varying starting ages (40-60), stopping ages (64-84) and intervals (1-4 years) were simulated. The number of quality adjusted life years (QALYs) gained and additional net costs (in €) per 1000 women were predicted (3.5% discounted) and incremental cost-effectiveness ratios (ICERs) were calculated to compare screening scenarios. Sensitivity analyses were performed using different assumptions. In total, 26 strategies covering all four intervals were on the efficiency frontier. Using a willingness-to-pay threshold of €20 000/QALY gained, the biennial 40 to 76 screening strategy was optimal. However, this strategy resulted in more overdiagnoses and false positives, and required a high screening capacity. The current strategy in the Netherlands, biennial 50 to 74 years, was dominated. Triennial screening in the age range 44 to 71 (ICER 9364) or 44 to 74 (ICER 11144) resulted in slightly more QALYs gained and lower costs than the current Dutch strategy. Furthermore, these strategies were estimated to require a lower screening capacity. Findings were robust when varying attendance and effectiveness of treatment. In conclusion, switching from biennial to triennial screening while simultaneously lowering the starting age to 44 can increase benefits at lower costs and with a minor increase in harms compared to the current strategy.

Reflecting on 20 years of breast cancer modeling in CISNET: Recommendations for future cancer systems modeling efforts.

Since 2000, the National Cancer Institute's Cancer Intervention and Surveillance Modeling Network (CISNET) modeling teams have developed and applied microsimulation and statistical models of breast cancer. Here, we illustrate the use of collaborative breast cancer multilevel systems modeling in CISNET to demonstrate the flexibility of systems modeling to address important clinical and policy-relevant questions. Challenges and opportunities of future systems modeling are also summarized. The 6 CISNET breast cancer models embody the key features of systems modeling by incorporating numerous data sources and reflecting tumor, person, and health system factors that change over time and interact to affect the burden of breast cancer. Multidisciplinary modeling teams have explored alternative representations of breast cancer to reveal insights into breast cancer natural history, including the role of overdiagnosis and race differences in tumor characteristics. The models have been used to compare strategies for improving the balance of benefits and harms of breast cancer screening based on personal risk factors, including age, breast density, polygenic risk, and history of Down syndrome or a history of childhood cancer. The models have also provided evidence to support the delivery of care by simulating outcomes following clinical decisions about breast cancer treatment and estimating the relative impact of screening and treatment on the United States population. The insights provided by the CISNET breast cancer multilevel modeling efforts have informed policy and clinical guidelines. The 20 years of CISNET modeling experience has highlighted opportunities and challenges to expanding the impact of systems modeling. Moving forward, CISNET research will continue to use systems modeling to address cancer control issues, including modeling structural inequities affecting racial disparities in the burden of breast cancer. Future work will also leverage the lessons from team science, expand resource sharing, and foster the careers of early stage modeling scientists to ensure the sustainability of these efforts.

The potential of breast cancer screening in Europe.

Currently, all European countries offer some form of breast cancer screening. Nevertheless, disparities exist in the status of implementation, attendance and the extent of opportunistic screening. As a result, breast cancer screening has not yet reached its full potential. We examined how many breast cancer deaths could be prevented if all European countries would biennially screen all women aged 50 to 69 for breast cancer. We calculated the number of breast cancer deaths already prevented due to screening as well as the number of breast cancer deaths which could be additionally prevented if the total examination coverage (organised plus opportunistic) would reach 100%. The calculations are based on total examination coverage in women aged 50 to 69, the annual number of breast cancer deaths for women aged 50 to 74 and the maximal possible mortality reduction from breast cancer, assuming similar effectiveness of organised and opportunistic screening. The total examination coverage ranged from 49% (East), 62% (West), 64% (North) to 69% (South). Yearly 21 680 breast cancer deaths have already been prevented due to mammography screening. If all countries would reach 100% examination coverage, 12 434 additional breast cancer deaths could be prevented annually, with the biggest potential in Eastern Europe. With maximum coverage, 23% of their breast cancer deaths could be additionally prevented, while in Western Europe it could be 21%, in Southern Europe 15% and in Northern Europe 9%. Our study illustrates that by further optimising screening coverage, the number of breast cancer deaths in Europe can be lowered substantially.

Effects of cancer screening restart strategies after COVID-19 disruption.

BACKGROUND: Many breast, cervical, and colorectal cancer screening programmes were disrupted due to the COVID-19 pandemic. This study aimed to estimate the effects of five restart strategies after the disruption on required screening capacity and cancer burden. METHODS: Microsimulation models simulated five restart strategies for breast, cervical, and colorectal cancer screening. The models estimated required screening capacity, cancer incidence, and cancer-specific mortality after a disruption of 6 months. The restart strategies varied in whether screens were caught up or not and, if so, immediately or delayed, and whether the upper age limit was increased. RESULTS: The disruption in screening programmes without catch-up of missed screens led to an increase of 2.0, 0.3, and 2.5 cancer deaths per 100 000 individuals in 10 years in breast, cervical, and colorectal cancer, respectively. Immediately catching-up missed screens minimised the impact of the disruption but required a surge in screening capacity. Delaying screening, but still offering all screening rounds gave the best balance between required capacity, incidence, and mortality. CONCLUSIONS: Strategies with the smallest loss in health effects were also the most burdensome for the screening organisations. Which strategy is preferred depends on the organisation and available capacity in a country.

The impact of the Covid-19 pandemic on breast cancer early detection and screening.

The COVID-19 pandemic affects mortality and morbidity, with disruptions expected to continue for some time, with access to timely cancer-related services a concern. For breast cancer, early detection and treatment is key to improved survival and longer-term quality of life. Health services generally have been strained and in many settings with population breast mammography screening, efforts to diagnose and treat breast cancers earlier have been paused or have had reduced capacity. The resulting delays to diagnosis and treatment may lead to more intensive treatment requirements and, potentially, increased mortality. Modelled evaluations can support responses to the pandemic by estimating short- and long-term outcomes for various scenarios. Multiple calibrated and validated models exist for breast cancer screening, and some have been applied in 2020 to estimate the impact of breast screening disruptions and compare options for recovery, in a range of international settings. On behalf of the Covid and Cancer Modelling Consortium (CCGMC) Working Group 2 (Breast Cancer), we summarize and provide examples of such in a range of settings internationally, and propose priorities for future modelling exercises. International expert collaborations from the CCGMC Working Group 2 (Breast Cancer) will conduct analyses and modelling studies needed to inform key stakeholders recovery efforts in order to mitigate the impact of the pandemic on early diagnosis and treatment of breast cancer.

Implementation Barriers to Value of Information Analysis in Health Technology Decision Making: Results From a Process Evaluation.

OBJECTIVES: Value of information (VOI) analysis can support health technology assessment decision making, but it is a long way from being standard use. The objective of this study was to understand barriers to the implementation of VOI analysis and propose actions to overcome these. METHODS: We performed a process evaluation of VOI analysis use within decision making on tomosynthesis versus digital mammography for use in the Dutch breast cancer population screening. Based on steering committee meeting attendance and regular meetings with analysts, we developed a list of barriers to VOI use, which were analyzed using an established diffusion model. We proposed actions to address these barriers. Barriers and actions were discussed and validated in a workshop with stakeholders representing patients, clinicians, regulators, policy advisors, researchers, and the industry. RESULTS: Consensus was reached on groups of barriers, which included characteristics of VOI analysis itself, stakeholder's attitudes, analysts' and policy makers' skills and knowledge, system readiness, and implementation in the organization. Observed barriers did not only pertain to VOI analysis itself but also to formulating the objective of the assessment, economic modeling, and broader aspects of uncertainty assessment. Actions to overcome these barriers related to organizational changes, knowledge transfer, cultural change, and tools. CONCLUSIONS: This in-depth analysis of barriers to implementation of VOI analysis and resulting actions and tools may be useful to health technology assessment organizations that wish to implement VOI analysis in technology assessment and research prioritization. Further research should focus on application and evaluation of the proposed actions in real-world assessment processes.

Modeling the natural history of ductal carcinoma in situ based on population data.

BACKGROUND: The incidence of ductal carcinoma in situ (DCIS) has increased substantially since the introduction of mammography screening. Nevertheless, little is known about the natural history of preclinical DCIS in the absence of biopsy or complete excision. METHODS: Two well-established population models evaluated six possible DCIS natural history submodels. The submodels assumed 30%, 50%, or 80% of breast lesions progress from undetectable DCIS to preclinical screen-detectable DCIS; each model additionally allowed or prohibited DCIS regression. Preclinical screen-detectable DCIS could also progress to clinical DCIS or invasive breast cancer (IBC). Applying US population screening dissemination patterns, the models projected age-specific DCIS and IBC incidence that were compared to Surveillance, Epidemiology, and End Results data. Models estimated mean sojourn time (MST) in the preclinical screen-detectable DCIS state, overdiagnosis, and the risk of progression from preclinical screen-detectable DCIS. RESULTS: Without biopsy and surgical excision, the majority of DCIS (64-100%) in the preclinical screen-detectable state progressed to IBC in submodels assuming no DCIS regression (36-100% in submodels allowing for DCIS regression). DCIS overdiagnosis differed substantially between models and submodels, 3.1-65.8%. IBC overdiagnosis ranged 1.3-2.4%. Submodels assuming DCIS regression resulted in a higher DCIS overdiagnosis than submodels without DCIS regression. MST for progressive DCIS varied between 0.2 and 2.5 years. CONCLUSIONS: Our findings suggest that the majority of screen-detectable but unbiopsied preclinical DCIS lesions progress to IBC and that the MST is relatively short. Nevertheless, due to the heterogeneity of DCIS, more research is needed to understand the progression of DCIS by grades and molecular subtypes.

Risk stratification in breast cancer screening: Cost-effectiveness and harm-benefit ratios for low-risk and high-risk women.

In mammography screening programmes, women are screened according to a one-size-fits-all principle. Tailored screening, based on risk levels, may lead to a better balance of benefits and harms. With microsimulation modelling, we determined optimal mammography screening strategies for women at lower (relative risk [RR] 0.75) and higher (RR 1.8) than average risk of breast cancer, eligible for screening, using the incremental cost-effectiveness ratio (ICER) of current uniform screening in the Netherlands (biennial [B] 50-74) as a threshold ICER. Strategies varied by interval (annual [A], biennial, triennial [T]) and age range. The number of life-years gained (LYG), breast cancer deaths averted, overdiagnosed cases, false-positive mammograms, ICERs and harm-benefit ratios were calculated. Optimal risk-based screening scenarios, below the threshold ICER of €8883/LYG, were T50-71 (€7840/LYG) for low-risk and B40-74 (€6062/LYG) for high-risk women. T50-71 screening in low-risk women resulted in a 33% reduction in false-positive findings, a similar reduction in costs and improved harm-benefit ratios compared to the current screening schedule. B40-74 in high-risk women led to an increase in screening benefit, compared to current B50-74 screening, but a relatively higher increase in false-positive findings. In conclusion, optimal screening consisted of a longer interval and lower stopping age than current uniform screening for low-risk women, and a lower starting age for high-risk women. Extending the interval for women at lower risk from biennial to triennial screening reduced harms and costs while maintaining most of the screening benefit.

Cost-effectiveness of Digital Breast Tomosynthesis in Population-based Breast Cancer Screening: A Probabilistic Sensitivity Analysis.

BackgroundDigital breast tomosynthesis (DBT) is a promising screening test, but its outcomes and cost-effectiveness remain uncertain.PurposeTo determine if biennial DBT is cost-effective in a screening setting, when compared with digital mammography (DM) in the Netherlands, and to quantify the uncertainty.Materials and MethodsIn this study, performed from March 2018 to February 2019, the MIcrosimulation SCreening ANalysis model was used to conduct a probabilistic sensitivity analysis (PSA), consisting of 10 000 model runs with 1 000 000 women simulated per run. The Bayesian Cost-Effectiveness Analysis package and the Sheffield Accelerated Value of Information tool were used to process PSA outcomes. Two simulated cohorts born in 1970 were invited to undergo biennial screening between ages 50 and 74 years-one cohort was assigned to DM screening, and one was assigned to DBT screening. DM input parameters were based on data from the Dutch breast cancer screening program. DBT parameters were based on literature and expert opinion. Willingness-to-pay thresholds of €20 000 ($22 000) and €35 000 ($38 500) per life-year gained (LYG) were considered. Effects and costs were discounted at 3.5% per year.ResultsDBT resulted in a gain of 13 additional life-years per 1000 women invited to screening (7% increase, 13 of 193), followed over lifetime, compared with DM and led to 2% (four of 159) fewer false-positive results. DBT screening led to incremental discounted lifetime effects of 5.09 LYGs (95% confidence interval: -0.80, 9.70) and an increase in lifetime costs of €137 555 ($151 311) per 1000 women (95% confidence interval: €31 093 [$34 202], €263 537 [$289 891]) compared with DM, resulting in a mean incremental cost-effectiveness ratio of €27 023 ($29 725) per LYG. The probability of DBT being more cost-effective was 0.36 at €20 000 and 0.66 at €35 000 per LYG.ConclusionSwitching from digital mammography to biennial digital breast tomosynthesis is not cost-effective at a willingness-to-pay threshold of €20 000 per life-year gained, but digital breast tomosynthesis has a higher probability of being more cost-effective than digital mammography at a threshold of €35 000 per life-year gained.© RSNA, 2020Online supplemental material is available for this article.See also the editorial by Slanetz in this issue.

Benefits and Harms of Mammography Screening for Women With Down Syndrome: a Collaborative Modeling Study.

BACKGROUND: Women with Down syndrome have a lower breast cancer risk and significantly lower life expectancies than women without Down syndrome. Therefore, it is not clear whether mammography screening strategies used for women without Down syndrome would benefit women with Down syndrome in the same way. OBJECTIVE: To determine the benefits and harms of various mammography screening strategies for women with Down syndrome using collaborative simulation modeling. DESIGN: Two established Cancer Intervention and Surveillance Modeling Network (CISNET) simulation models estimated the benefits and harms of various screening strategies for women with Down syndrome over a lifetime horizon. PARTICIPANTS: We modeled a hypothetical cohort of US women with Down syndrome who were born in 1970. INTERVENTIONS: Annual, biennial, triennial, and one-time digital mammography screenings during the ages 40-74. MAIN MEASURES: The models estimated numbers of mammograms, false-positives, benign biopsies, breast cancer deaths prevented, and life-years gained per 1000 screened women when compared with no screening. KEY RESULTS: In average-risk women 50-74, biennial screening incurred 122 mammograms, 10 false-positive mammograms, and 1.4 benign biopsies per one life-year gained compared with no screening. In women with Down syndrome, the same screening strategy incurred 2752 mammograms, 242 false-positive mammograms, and 34 benign biopsies per one life-year gained compared with no screening. The harm/benefit ratio varied for other screening strategies, and was most favorable for one-time screening at age 50, which incurred 1629 mammograms, 144 false-positive mammograms, and 20 benign biopsies per one life-year gained compared with no screening. CONCLUSIONS: The harm/benefit ratios for various mammography screening strategies in women with Down syndrome are not as favorable as those for average-risk women. The benefit of screening mammography for women with Down syndrome is less pronounced due to lower breast cancer risk and shorter life expectancy.

Detection and interval cancer rates during the transition from screen-film to digital mammography in population-based screening.

BACKGROUND: Between 2003 and 2010 digital mammography (DM) gradually replaced screen-film mammography (SFM) in the Dutch breast cancer screening programme (BCSP). Previous studies showed increases in detection rate (DR) after the transition to DM. However, national interval cancer rates (ICR) have not yet been reported. METHODS: We assessed programme sensitivity and specificity during the transition period to DM, analysing nationwide data on screen-detected and interval cancers. Data of 7.3 million screens in women aged 49-74, between 2004 and 2011, were linked to the Netherlands Cancer Registry to obtain data on interval cancers. Age-adjusted DRs, ICRs and recall rates (RR) per 1000 screens and programme sensitivity and specificity were calculated by year, age and screening modality. RESULTS: 41,662 screen-detected and 16,160 interval cancers were analysed. The DR significantly increased from 5.13 (95% confidence interval (CI):5.00-5.30) in 2004 to 6.34 (95% CI:6.15-6.47) in 2011, for both in situ (2004:0.73;2011:1.24) and invasive cancers (2004:4.42;2011:5.07), whereas the ICR remained stable (2004: 2.16 (95% CI2.06-2.25);2011: 2.13 (95% CI:2.04-2.22)). The RR changed significantly from 14.0 to 21.4. Programme sensitivity significantly increased, mainly between ages 49-59, from 70.0% (95% CI:68.9-71.2) to 74.4% (95% CI:73.5-75.4) whereas specificity slightly declined (2004:99.1% (95% CI:99.09-99.13);2011:98.5% (95% CI:98.45-98.50)). The overall DR was significantly higher for DM than for SFM (6.24;5.36) as was programme sensitivity (73.6%;70.1%), the ICR was similar (2.19;2.20) and specificity was significantly lower for DM (98.5%;98.9%). CONCLUSIONS: During the transition from SFM to DM, there was a significant rise in DR and a stable ICR, leading to increased programme sensitivity. Although the recall rate increased, programme specificity remained high compared to other countries. These findings indicate that the performance of DM in a nationwide screening programme is not inferior to, and may be even better, than that of SFM.

Association of Screening and Treatment With Breast Cancer Mortality by Molecular Subtype in US Women, 2000-2012.

Importance: Given recent advances in screening mammography and adjuvant therapy (treatment), quantifying their separate and combined effects on US breast cancer mortality reductions by molecular subtype could guide future decisions to reduce disease burden. Objective: To evaluate the contributions associated with screening and treatment to breast cancer mortality reductions by molecular subtype based on estrogen-receptor (ER) and human epidermal growth factor receptor 2 (ERBB2, formerly HER2 or HER2/neu). Design, Setting, and Participants: Six Cancer Intervention and Surveillance Network (CISNET) models simulated US breast cancer mortality from 2000 to 2012 using national data on plain-film and digital mammography patterns and performance, dissemination and efficacy of ER/ERBB2-specific treatment, and competing mortality. Multiple US birth cohorts were simulated. Exposures: Screening mammography and treatment. Main Outcomes and Measures: The models compared age-adjusted, overall, and ER/ERBB2-specific breast cancer mortality rates from 2000 to 2012 for women aged 30 to 79 years relative to the estimated mortality rate in the absence of screening and treatment (baseline rate); mortality reductions were apportioned to screening and treatment. Results: In 2000, the estimated reduction in overall breast cancer mortality rate was 37% (model range, 27%-42%) relative to the estimated baseline rate in 2000 of 64 deaths (model range, 56-73) per 100 000 women: 44% (model range, 35%-60%) of this reduction was associated with screening and 56% (model range, 40%-65%) with treatment. In 2012, the estimated reduction in overall breast cancer mortality rate was 49% (model range, 39%-58%) relative to the estimated baseline rate in 2012 of 63 deaths (model range, 54-73) per 100 000 women: 37% (model range, 26%-51%) of this reduction was associated with screening and 63% (model range, 49%-74%) with treatment. Of the 63% associated with treatment, 31% (model range, 22%-37%) was associated with chemotherapy, 27% (model range, 18%-36%) with hormone therapy, and 4% (model range, 1%-6%) with trastuzumab. The estimated relative contributions associated with screening vs treatment varied by molecular subtype: for ER+/ERBB2-, 36% (model range, 24%-50%) vs 64% (model range, 50%-76%); for ER+/ERBB2+, 31% (model range, 23%-41%) vs 69% (model range, 59%-77%); for ER-/ERBB2+, 40% (model range, 34%-47%) vs 60% (model range, 53%-66%); and for ER-/ERBB2-, 48% (model range, 38%-57%) vs 52% (model range, 44%-62%). Conclusions and Relevance: In this simulation modeling study that projected trends in breast cancer mortality rates among US women, decreases in overall breast cancer mortality from 2000 to 2012 were associated with advances in screening and in adjuvant therapy, although the associations varied by breast cancer molecular subtype.